/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

/*!
 * \file np_location_scale_op.cc
 * \brief Implementation of the API of functions in src/operator/numpy/random/np_location_scale_op.h
 */
#include <mxnet/api_registry.h>
#include <mxnet/runtime/packed_func.h>
#include <vector>
#include "../../utils.h"
#include "../../../../operator/numpy/random/np_location_scale_op.h"

namespace mxnet {

int scalar_number(const runtime::MXNetArgs& args) {
  int result = 0;
  if (args[0].type_code() == kDLFloat || args[0].type_code() == kDLInt)
    result++;
  if (args[1].type_code() == kDLFloat || args[1].type_code() == kDLInt)
    result++;
  return result;
}

MXNET_REGISTER_API("_npi.gumbel")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      const nnvm::Op* op = Op::Get("_npi_gumbel");
      op::NumpyLocationScaleParam param;
      nnvm::NodeAttrs attrs;
      attrs.op = op;
      if (args[2].type_code() == kDLInt) {
        param.size = Tuple<index_t>(1, args[2].operator int64_t());
      } else if (args[2].type_code() == kNull) {
        param.size = dmlc::optional<mxnet::Tuple<index_t>>();
      } else {
        param.size = Tuple<index_t>(args[2].operator ObjectRef());
      }
      if (args[3].type_code() != kNull) {
        attrs.dict["ctx"] = args[3].operator std::string();
      }
      NDArray* out      = args[4].operator mxnet::NDArray*();
      NDArray** outputs = out == nullptr ? nullptr : &out;
      int num_outputs   = out != nullptr;
      int scalar        = scalar_number(args);
      std::vector<NDArray*> inputs;
      int num_inputs = 0;
      if (scalar == 2) {
        param.loc   = args[0].operator double();
        param.scale = args[1].operator double();
      } else if (scalar == 0) {
        param.loc   = dmlc::nullopt;
        param.scale = dmlc::nullopt;
        inputs.push_back(args[0].operator mxnet::NDArray*());
        inputs.push_back(args[1].operator mxnet::NDArray*());
        num_inputs = 2;
      } else {
        if (args[0].type_code() == kDLFloat || args[0].type_code() == kDLInt) {
          param.loc   = args[0].operator double();
          param.scale = dmlc::nullopt;
          inputs.push_back(args[1].operator mxnet::NDArray*());
        } else {
          param.loc   = dmlc::nullopt;
          param.scale = args[1].operator double();
          inputs.push_back(args[0].operator mxnet::NDArray*());
        }
        num_inputs = 1;
      }
      attrs.parsed = param;
      SetAttrDict<op::NumpyLocationScaleParam>(&attrs);
      auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, outputs);
      if (out) {
        *ret = PythonArg(4);
      } else {
        *ret = ndoutputs[0];
      }
    });

MXNET_REGISTER_API("_npi.logistic")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      const nnvm::Op* op = Op::Get("_npi_logistic");
      op::NumpyLocationScaleParam param;
      nnvm::NodeAttrs attrs;
      attrs.op = op;
      if (args[2].type_code() == kDLInt) {
        param.size = Tuple<index_t>(1, args[2].operator int64_t());
      } else if (args[2].type_code() == kNull) {
        param.size = dmlc::nullopt;
      } else {
        param.size = Tuple<index_t>(args[2].operator ObjectRef());
      }
      if (args[3].type_code() != kNull) {
        attrs.dict["ctx"] = args[3].operator std::string();
      }
      NDArray* out      = args[4].operator mxnet::NDArray*();
      NDArray** outputs = out == nullptr ? nullptr : &out;
      int num_outputs   = out != nullptr;
      int scalar        = scalar_number(args);
      std::vector<NDArray*> inputs;
      int num_inputs = 0;
      if (scalar == 2) {
        param.loc   = args[0].operator double();
        param.scale = args[1].operator double();
      } else if (scalar == 0) {
        param.loc   = dmlc::nullopt;
        param.scale = dmlc::nullopt;
        inputs.push_back(args[0].operator mxnet::NDArray*());
        inputs.push_back(args[1].operator mxnet::NDArray*());
        num_inputs = 2;
      } else {
        if (args[0].type_code() == kDLFloat || args[0].type_code() == kDLInt) {
          param.loc   = args[0].operator double();
          param.scale = dmlc::nullopt;
          inputs.push_back(args[1].operator mxnet::NDArray*());
        } else {
          param.loc   = dmlc::nullopt;
          param.scale = args[1].operator double();
          inputs.push_back(args[0].operator mxnet::NDArray*());
        }
        num_inputs = 1;
      }
      attrs.parsed = param;
      SetAttrDict<op::NumpyLocationScaleParam>(&attrs);
      auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, outputs);
      if (out) {
        *ret = PythonArg(4);
      } else {
        *ret = ndoutputs[0];
      }
    });

}  // namespace mxnet
